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Wednesday, August 19, 2009

Finding the right proportion of resources for knowledge sharing

Walt Warnick and David Wojick, The Knowledge Investment Curve, OSTIblog, August 19, 2009.

Every scientist knows that science advances only if knowledge is shared. Mathematically, this statement implies that the advance of science is a function of both the sharing of research results, as well as doing the original research. In principle, therefore, decision makers face the problem of deciding how much to spend on original research and how much to spend on sharing the knowledge that comes out of research.

Consider the accompanying graph with the x-axis being the fraction of research resources expended on spreading knowledge. The scale would range from 0% to 100%. The y-axis is the pace of scientific discovery. One can imagine a curve plotting the pace of discovery as a function of the fraction of resources expended on sharing knowledge.

When the fraction of resources is 0%, the pace of science advance is zero, as nothing is shared. When the fraction of resources is 100%, the pace of advance is also zero, as nothing is spent on the research itself. In between these endpoints, the plot will have a maximum. The plot is the Knowledge Investment Curve.

... [W]e know very little about the actual form of this curve, or even how much is currently invested in sharing. ...

[The] myriad activities [of knowledge sharing] are centuries old, as old as science itself. What each costs in the aggregate we have little idea. We do know that scientific journals cost several billion dollars a year ...

We also know that the Internet, especially the World Wide Web, is changing the nature of the equation ...

We can ask then what the federal investment should be in Web-based science sharing? ... One thing we know is that the investment in sharing is highly uneven across the various sciences. The fraction of health science research funding dedicated to sharing knowledge is greater than for physical and energy sciences. The latter is unlikely to be near the optimum.